In a machine-to-machine (M2M) ecosystem, one of the possibilities with Networked Society, there will be billions of M2M Devices relating to various services and applications. A networked society would comprise of billions of connections. Mobile phone subscriptions may surpass world population by 2015. M2M connections are expected to increase 3-4 times by 2019. Each year, telecommunication network operators spend around USD 15 billion in dealing with outages and disruptions. Outages can be of different types like service, application, network, power or device outages. Outage recovery intelligence in a networked society involving billions of devices is an emerging focus area for operators.
As per the European Telecommunications Standards Institute (ETSI) M2M specification, the M2M functional architecture is as given in FIG. 1. A M2M device may be defined as a device that runs M2M Application(s) using M2M Service Capabilities. M2M devices can be stationary, mobile, main powered or battery powered. M2M Devices connect to Network Domain in accordance with either case 1 or case 2 below and as illustrated in FIG. 1.
Case 1—“Direct Connectivity”: M2M devices connect to the network domain via the access network. The M2M device performs the procedures such as registration, authentication, authorization, management and provisioning with the network domain. The M2M device may provide services to other devices (e.g. legacy devices) connected to it that are hidden from the network domain.
Case 2—“Gateway as a Network Proxy”: The M2M device connects to the network domain via an M2M gateway. M2M devices connect to the M2M gateway using the M2M area network. The M2M gateway acts as a proxy for the network domain towards the M2M devices that are connected to it. Examples of procedures that use proxies include: authentication, authorization, management, and provisioning. M2M devices may be connected to the network domain via multiple M2M gateways.
Some examples of machine type communication applications are listed in the following table 1. This list is not exhaustive and is intended to be indicative of the scope of machine type communication applications.
TABLE 1Service AreaMTC applicationsSecuritySurveillance systemsBackup for landlineControl of physical access (e.g. to buildings)Car/driver securityTracking & TracingFleet ManagementOrder ManagementPay as you driveAsset TrackingNavigationTraffic informationRoad tollingRoad traffic optimization/steeringPaymentPoint of salesVending machinesGaming machinesHealthMonitoring vital signsSupporting the aged or handicappedWeb Access Telemedicine pointsRemote diagnosticsRemoteSensorsMaintenance/ControlLightingPumpsValvesElevator controlVending machine controlVehicle diagnosticsMeteringPowerGasWaterHeatingGrid controlIndustrial meteringConsumer DevicesDigital photo frameDigital cameraeBook
As per current state of art, device connectivity is managed by operators using products like the Ericsson Device Connection Platform (DCP) which is a cloud service enabling operators to offer connectivity management to enterprise customers, or another hosted core network (CN) or home public land mobile network (Home PLMN or HPLMN) which may be used by several different network operators to manage subscriptions for radio devices. The platform supports operators in building up the M2M business from three perspectives, managed connectivity through the life cycle, sales preparation and business expansion. Thus, such a hosted network may host a multi-tenant home location register (HLR) and other core network nodes (Gateway General Packet Radio Service (GPRS) support node (GGSN), short message service centre (SMSC), etc.) in HPLMN as a core network service for all customer operators. All the M2M subscribers of the operators may be registered and stored on hosted HLR. Connectivity may be provided as a service to all operators hosted on the platform. On top of the core network service, also a cloud business support system (BSS) may be hosted to provision and manage subscriber data, processes, billing, etc.
A device first connects to the network; a connected device is then able to participate in request/response messages with other nodes in interaction. If there is an outage, then devices disconnect from the network. Once the outage is over, disconnected devices reconnect back to the network to resume what they were doing before the outage.
Temporal networks are commonly used to represent systems where connections have the dimension of time: such as telecommunication, neural signal processing, biochemical reactions and human social interaction networks. For instance, calls made between different user nodes at various timestamps can be represented using a temporal graph.
During outages, millions of devices (or graph nodes/vertices) disappear (are disconnected) from the network and once the outage is over those devices reconnect over a certain amount of time. Since the network performance may vary at different location due to change in signal strength, bandwidth, quality of service (QoS), cell site performance parameters, the reconnection pattern is typically not uniform. This leads to differences in re-connection patterns of billions of M2M devices/device-groups spread across the operator's network. During outage recovery, understanding such reconnection patterns of devices to a network will help an operator of the network to manage network resources efficiently.